The Annals of Applied Statistics

Goodness of fit in nonlinear dynamics: Misspecified rates or misspecified states?

Giles Hooker and Stephen P. Ellner

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Abstract

This paper introduces diagnostic tests for the nature of lack of fit in ordinary differential equation models (ODEs) proposed for data. We present a hierarchy of three possible sources of lack of fit: unaccounted-for stochastic variation, misspecification of functional forms in rate equations, and omission of dynamic variables in the description of the system. We represent lack of fit by allowing a parameter vector to vary over time, and propose generic testing procedures that do not rely on specific alternative models. Instead, different sources for lack of fit are characterized in terms of nonparametric relationships among latent variables. The tests are carried out through a combination of residual bootstrap and permutation methods. We demonstrate the effectiveness of these tests on simulated data and on real data from laboratory ecological experiments and electro-cardiogram data.

Article information

Source
Ann. Appl. Stat. Volume 9, Number 2 (2015), 754-776.

Dates
Received: December 2013
Revised: December 2014
First available in Project Euclid: 20 July 2015

Permanent link to this document
http://projecteuclid.org/euclid.aoas/1437397110

Digital Object Identifier
doi:10.1214/15-AOAS828

Mathematical Reviews number (MathSciNet)
MR3371334

Zentralblatt MATH identifier
06499929

Keywords
Differential equation diagnostics goodness of fit attractor reconstruction bootstrap

Citation

Hooker, Giles; Ellner, Stephen P. Goodness of fit in nonlinear dynamics: Misspecified rates or misspecified states?. Ann. Appl. Stat. 9 (2015), no. 2, 754--776. doi:10.1214/15-AOAS828. http://projecteuclid.org/euclid.aoas/1437397110.


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Supplemental materials

  • Supplementary material for “Goodness of fit in nonlinear dynamics: Misspecified rates or misspecified states?”. This appendix provides supporting material which includes the following: details of the chemostat models used to generate data for Section 6 and background material on the generalized profiling methods of Ramsay et al. (2007), along with simulation experiments using this method instead of gradient matching.